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8h 30min

Updated 3 weeks ago

The Hacker's Guide to Scaling Python
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Learn about Python's scalability, concurrency, and distribution via CPU scaling, event loops, queue-based distribution, and building REST APIs to optimize and deploy high-performance applications.
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Python, in all of its greatness, is often dismissed when needing to write performant and distributed applications. It’s considered to be slow and not suited for the task. In this course, you will find that with the right implementation of Python, you can write applications that scale horizontally, perform well, and are distributed. To kick things off, you’ll learn about CPU scaling, concurrency, and event loops, all of which are crucial for implementing a distributed system. After that, you’ll move on to queue-based distribution, lock management, and group memberships, which are fundamental concepts for maintaining availability and consistency in distributed applications. In the last half, you’ll learn how to build a REST API, how to deploy your app to a PaaS, and how to optimize your application's performance. By the end of this course, you’ll be more productive with Python, you’ll be able to write faster applications that are distributed, and you’ll have a great new skill that is highly coveted.
Python, in all of its greatness, is often dismissed when needing to write performant and distributed applications. It’s consider...Show More

Content

1.

Scaling

5 Lessons

Step through scaling Python applications using multithreading, distributing systems, and service-oriented architecture.

3.

Event Loops

7 Lessons

Work your way through event loops, asynchronous code, and efficient network management using asyncio.

6.

Designing for Failure

5 Lessons

Tackle exception handling, retry strategies, and Tenacity for robust Python applications.

7.

Project Walkthrough

1 Lessons

Practice using Celery and Redis to efficiently manage and process tasks.

11.

Deploying on PaaS

7 Lessons

Break down the steps to deploying Python applications on various PaaS platforms.

12.

Testing Distributed Systems

5 Lessons

Map out the steps for testing, environment setup, and service management in distributed systems.

13.

Caching

7 Lessons

Investigate caching to enhance Python app performance, covering local, memoization, and distributed methods.

14.

Performance

8 Lessons

Master the steps to optimize Python performance through profiling, disassembling code, and efficient memory use.

15.

Conclusion

1 Lessons

Engage in practical projects to apply your scalable Python skills confidently.
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Developed by MAANG Engineers
Every Educative resource is designed by our in-house team of ex-MAANG software engineers and PhD computer science educators — subject matter experts who’ve shipped production code at scale and taught the theory behind it. The goal is to get you hands-on with the skills you need to stay ahead in today's constantly evolving tech landscape. No videos, no fluff — just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

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